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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- go_emotions
metrics:
- accuracy
model-index:
- name: sentiment-model-sample-27go-emotion
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: go_emotions
type: go_emotions
args: simplified
metrics:
- name: Accuracy
type: accuracy
value: 0.5888888888888889
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# sentiment-model-sample-27go-emotion
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the go_emotions dataset.
It achieves the following results on the evaluation set:
- Loss: 4.1765
- Accuracy: 0.5889
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
### Training results
### Framework versions
- Transformers 4.17.0
- Pytorch 1.10.0+cu111
- Datasets 2.0.0
- Tokenizers 0.12.0